Logo Detection using Deep Learning

Logo Detection using Deep Learning OpenCV | Python

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SKU: PAN_OPCV_016 Categories: , , , , , ,

Description

Logo Detection using Deep Learning OpenCV

The receiver consists of eight data lines plus one forwarded-clock lane supporting the hyper transport standard for high-density chip-to-chip links. This all-digital clock and data recovery (ADCDR) circuit, which is well suited for today’s CMOS process scaling, enables the receiver to achieve low power and area consumption. The ADCDR can enter into an open loop after lock-in to save power and avoid the clock dithering phenomenon. Moreover, to compensate for the open-loop, a phase tracking procedure is proposed to enable the ADCDR to track the phase drift due to the voltage and temperature variations. Furthermore, the all-digital delay-locked loop circuit integrated into the ADCDR can generate accurate multiphase clocks with the proposed calibrated locking algorithm in the presence of process variations.Logo Detection using Deep Learning OpenCV

Introduction:

HIGH-DENSITY forwarded-clock (FC) links have been widely used in the multi-core processor’s interfaces for the chip-to-chip interconnects, such as Quick-Path Interconnect (QPI), hyper transport, and DDR standards. A dedicated clock is delivered from the transmitter to the receiver and shared by multiple data lanes. Although the additional clock lane consumes extra pins, area, and power, all of these can be amortized among many data lanes. The clock and data recovery (CDR) circuit in the FC receiver is used to align the received clock with the data for error-free sampling and it has become the most critical and power/area-hungry component in the receiver.

Existing System:

Ring-oscillator-based calibration: This system gives to guarantee accurate phase relationships in the presence of process variations using separated delay codes for each sub-delay line. Unfortunately, the ring oscillator formed by the sub-delay line during calibration has to run at a multiplying frequency of the reference clock.

Drawback:

Difficult to satisfy the timing constraint in high-speed applications and become much worse when more multi-phase clocks are demanded.

Proposed System:

Calibration method: A simpler and more effective calibration method is proposed to eliminate process mismatch with negligible penalties of the area, power, and performance. To track the phase shift due to the voltage and temperature variations, all-digital DLLs/CDRs need to continue working in the close loop after lock-in. However, the clock phase will remain being adjusted according to the closed-loop early/late feedback and moving backward and forward, which is called clock dithering. Logo Detection using Deep Learning OpenCV

Design: All-digital DLL-based clock generator

Simulation Tool:

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